• The Journal of Korean Physical Therapy
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• v.22 no.4
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• pp.7-14
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• 2010

Purpose: The goal of this study was to investigate the effect of balance and gait ability through two motor dual task training in chronic stroke subjects. Methods: A group of twenty-five subjects who were six months post stroke participated in this study, where they were designated into pretest-posttest control The subjects were randomly allocated into two groups: experimental (n=13) and control (n=12). Both groups received physical therapy for 5 session 30 minutes per week during 6 weeks. Experimental group practiced additional two motor dual task training programs for thirty minutes a day, three days a week during six weeks. Evaluation of results was obtained through analyzing static balance, dynamic balance and gait function. Results: There was significant improvement among the group that practiced the additional two motor dual task training in that the postural sway area with open eye and close eye on the foam surface, the dynamic balance (p<0.05), and the gait function (p<0.05). Conclusion: Two motor dual task training improved static balance on the foam, dynamic balance, gait function. These results suggest that two motor dual task training is a feasible and suitable treatment for individuals with chronic stroke.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.393-397
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• 2001

This paper addresses an Intelligent Agent-based Open Architecture Cell Controller for Intelligent Manufacturing System(IMS). With an Intelligent Agent approach, the IMS will be a independent, autonomous, distributed system and achieve a adaptability to change of manufacturing environment. As the development methodology of Open Architecture Cell Controller, an object-oriented modeling technique is employed for building models associated with IMS operation, such as resource model, product model, and control model. Intelligent Agent-based Open Architecture Cell Controller consists of two kinds of dependant agents, that are the active agent and the coordinator agent. The Active agent is contributed to control components of IMS in real-time. The coordinator agent has great role in scheduling and planning of IMS. It communicates with other active agents to get information about status on system and generates the next optimal task through the making-decision logic and dispatch it to other active agent.

• Smart Structures and Systems
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• v.23 no.6
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• pp.553-564
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• 2019

Modeling of magnetorheological (MR) dampers for cable vibration control to facilitate the design of even more effective and economical systems is still a challenging task. In this study, a parameter-adaptive three-element model is first established for a full-scale MR damper based on laboratory tests. The parameters of the model are represented by a set of empirical formulae in terms of displacement amplitude, voltage input, and excitation frequency. The model is then incorporated into the governing equation of cable-damper system for investigation of open-loop vibration control of stay cables in a cable-stayed bridge. The concept of optimal voltage/current input achieving the maximum damping for the system is put forward and verified. Multi-mode suboptimal and Single-mode optimal open-loop control method is then developed. Important conclusions are drawn on application issues and unique characteristics of open-loop cable vibration control using MR dampers.

• Education of Primary School Mathematics
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• v.14 no.2
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• pp.117-134
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• 2011

The purpose of this research was to analyze mathematical task types to enhance creativity. Creativity is increasingly important in every field of disciplines and industries. To be excel in the 21st century, students need to have habits to think creatively in mathematics learning. The method of the research was to collect the previous research and papers concerning creativity and mathematics. To search the materials, the researcher used the search engines such as the GIL and the KISTI. The mathematical task types to enhance creativity were categorized 16 different types according to their forms and characteristics. The types of tasks include (1) requiring various strategies, (2) requiring preferences on strategies, (3) making word problems, (4) making parallel problems, (5) requiring transforming problems, (6) finding patterns and making generalization, (7) using open-ended problems, (8) asking intuition for final answers, (9) asking patterns and generalization (10) requiring role plays, (11) using literature, (12) using mathematical puzzles and games, (13) using various materials, (14) breaking patterned thinking, (15) integrating among disciplines, and (16) encouraging to change our lives. To enhance students' creativity in mathematics teaching and learning, the researcher recommended the followings: reshaping perspectives toward teaching and learning, developing and providing creativity-rich tasks, applying every day life, using open-ended tasks, using various types of tasks, having assessment ability, changing assessment system, and showing and doing creative thinking and behaviors of teachers and parents.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.781-790
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• 2020

This study's primary purpose is to explore the psychological capital roles and personality traits of Big-Five in predicting OCB (organizational citizenship behavior) and performance of task in Indonesia's electricity sector. The data were gathered from the employees of four major cities in Indonesia, in Southeast Sulawesi, comprising 246 employees. The data were analyzed utilizing a PLS (partial least squares) based SEM (structural equation modeling) technique. The findings indicate that the psychological capital and personality traits of Big-Five relate significantly to OCB and the performance of task. Nevertheless, against our expectations, OCB does not significantly relate to the performance of task. This study also discusses the findings' further implications. In terms of practical implications, the findings of this research stipulate that psychological capital and Big-Five personality traits aimed to improve employee performance and can be most effective if specifically targeted at OCB. Given that both variables play an important role to promote OCB, caring training initiatives that focus on mutual help can be very valuable for organizational improvement. In a managerial perspective, organizations can increase OCB by conducting open communication strategies between managers and employees to further stimulate and strengthen the ability of employees to display extra-role behaviors.

• Journal of Korean Academy of Nursing Administration
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• v.13 no.2
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• pp.156-166
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• 2007

Purpose: The purpose of the present study was to examine the causal relationships among hospital nursing organizational characteristics (organizational climate, workload), individual characteristics (experience, education) and outcome variables (job satisfaction, job stress, task performance) by constructing and testing a conceptual framework. Method: Five large general hospitals located in Seoul were selected to participated. The total sample of 245 registered nurses represents a response rate of 94 percent. Data for this study was collected from January to February in 2006 by questionnaire. Path analyses with LISREL program were used to test the fit of the proposed model to the data and to examine the causal relationships among variables. Result: Both the proposed model and the modified model fit the data excellently. The model revealed relatively high explanatory power of work stress (40%), job satisfaction (46%) and task performance (27%) by predicted variables. In predicting work stress, job satisfaction and task performance, the finding of this study clearly demonstrate organizational climate might be the most important variable. Conclusion: Based on the findings of the study, it was suggested that desirable organizational climate was needed to increase the nurses' mental and physical health as well as qualified task performance.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.163-172
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• 2022

The interconnection of an enormous number of devices into the Internet at a massive scale is a consequence of the Internet of Things (IoT). As a result, tasks offloading from these IoT devices to remote cloud data centers become expensive and inefficient as their number and amount of its emitted data increase exponentially. It is also a challenge to optimize IoT device energy consumption while meeting its application time deadline and data delivery constraints. Consequently, Fog Computing was proposed to support efficient IoT tasks processing as it has a feature of lower service delay, being adjacent to IoT nodes. However, cloud task offloading is still performed frequently as Fog computing has less resources compared to remote cloud. Thus, optimized schemes are required to correctly characterize and distribute IoT devices tasks offloading in a hybrid IoT, Fog, and cloud paradigm. In this paper, we present a detailed survey and classification of of recently published research articles that address the energy efficiency of task offloading schemes in IoT-Fog-Cloud paradigm. Moreover, we also developed a taxonomy for the classification of these schemes and provided a comparative study of different schemes: by identifying achieved advantage and disadvantage of each scheme, as well its related drawbacks and limitations. Moreover, we also state open research issues in the development of energy efficient, scalable, optimized task offloading schemes for Fog computing.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.2
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• pp.10-18
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• 1997

This paper presents the development of real-time estimation and control details for a computer vision-based robot control method. This is accomplished using a sequential estimation scheme that permits placement of these points in each of the two-dimensional image planes of monitoring cameras. Estimation model is developed based on a model that generalizes know 4-axis Scorbot manipulator kinematics to accommodate unknown relative camera position and orientation, etc. This model uses six uncertainty-of-view parameters estimated by the iteration method. The method is tested experimentally in two ways : First the validity of estimation model is tested by using the self-built test model. Second, the practicality of the presented control method is verified in performing 4-axis manipulator's assembly task. These results show that control scheme used is precise and robust. This feature can open the door to a range of application of multi-axis robot such as deburring and welding.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.6
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• pp.325-334
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• 2016

Recently, Open Computing Language (OpenCL) has been proposed to provide a framework that supports heterogeneous computing platforms. By using an OpenCL framework, digital communication systems can support various protocols in a unified computing environment to achieve both high portability and high performance. This article introduces a parallel software decoder of Low Density Parity Check (LDPC) codes for China Multimedia Mobile Broadcasting (CMMB) on a heterogeneous platform. Each step of LDPC decoding has different parallelization characteristics. In this paper, steps suitable for task-level parallelization are executed on the CPU, and steps suitable for data-level parallelization are processed by the GPU. To improve the performance of the proposed OpenCL kernels for LDPC decoding operations, explicit thread scheduling, loop-unrolling, and effective data transfer techniques are applied. The proposed LDPC decoder achieves high performance by using heterogeneous multi-core processors on a unified computing framework.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4103-4121
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• 2018

Quality of Service (QoS) awareness is recognized as a key point for the success of Internet of Things (IOT).Realizing the full potential of the Internet of Things requires, a real-time task scheduling algorithm must be designed to meet the QoS need. In order to schedule tasks with diverse QoS requirements in cloud environment efficiently, we propose a task scheduling strategy based on dynamic priority and load balancing (DPLB) in this paper. The dynamic priority consisted of task value density and the urgency of the task execution, the priority is increased over time to insure that each task can be implemented in time. The scheduling decision variable is composed of time attractiveness considered earliest completion time (ECT) and load brightness considered load status information which by obtain from each virtual machine by topic-based publish/subscribe mechanism. Then sorting tasks by priority and first schedule the task with highest priority to the virtual machine in feasible VMs group which satisfy the QoS requirements of task with maximal. Finally, after this patch tasks are scheduled over, the task migration manager will start work to reduce the load balancing degree.The experimental results show that, compared with the Min-Min, Max-Min, WRR, GAs, and HBB-LB algorithm, the DPLB is more effective, it reduces the Makespan, balances the load of VMs, augments the success completed ratio of tasks before deadline and raises the profit of cloud service per second.